多个传感器容错的预测控制,用于自主地表车辆的形成
Wenxiang Wu1, Chenguang Liu2, Xiumin Chu2
1State Key Laboratory of Maritime Technology and Safety, Wuhan University of Technology, Wuhan, 430063, China; School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan, 430063, China.
ISA transactions
|August 7, 2025
概括
这项研究引入了自主地表车辆 (ASV) 车队的新故障耐受性控制方法,尽管传感器故障,但加强了合作控制. DEKF-MPC方法确保了准确的轨迹跟踪和ASV的航向维护.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 海洋工程 海洋工程
- 容错系统 容错系统
背景情况:
- 自主地表车辆 (ASV) 的合作控制受到多个传感器故障的挑战,影响导航和形成稳定性.
- 现有的方法在动态和多个传感器退化场景下努力保持强大的形成控制.
研究的目的:
- 为ASV形成路径在多个传感器故障下提出预测性故障耐受性控制策略.
- 在传感器异常存在时,提高ASV合作控制系统的可靠性和准确性.
主要方法:
- 开发一个分布式扩展卡尔曼波器 (DEKF) 状态估计器,集成来自其他ASV的故障检测和辅助数据.
- 实施一个模型预测控制 (MPC) 控制器,利用DEKF估计的状态来实现稳健的轨迹跟踪.
- 使用虚拟领袖-追随者结构建立ASV形成路径的模型.
主要成果:
- 拟议的DEKF-MPC方法在模拟中显示出与APF-MPC和RANSAC-EKF-MPC相比的优越性能.
- 准确的轨迹跟踪和一致的航向维护是ASVs实现的,即使有多个传感器故障.
- DEKF状态估计器有效估计了ASV位置,通过水的速度 (STW) 和故障条件下的当前速度.
结论:
- DEKF-MPC策略提供了一个有效的解决方案,用于对ASV结构的故障耐受性合作控制.
- 这种方法显著提高了在复杂的海洋环境中运行的ASV系统的稳定性和可靠性,传感器不确定性.
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